An Overview of Apache Cassandra
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Apache Cassandra is a free, distributed, open source, and highly scalable NoSQL database that is designed to handle large amounts of data across many commodity servers. It provides high availability with no single point of failure, linear scalability, and tunable consistency. Cassandra's architecture allows it to spread data across a cluster of servers and replicate across multiple data centers for fault tolerance. It is used by many large companies for applications that require high performance, scalability, and availability.
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An Overview of Apache Cassandra
- 1. Cassandra Essentials Tutorial Series An Overview of Apache Cassandra
- 2. Agenda What is Cassandra? History Architecture Key Features and Benefits Who’s using Cassandra? Where to get Cassandra
- 3. Definition of Cassandra Apache Cassandra™ is a free Distributed… High performance… Extremely scalable… Fault tolerant (i.e. no single point of failure)… post-relational database solution. Cassandra can serve as both real-time datastore (the “system of record”) for online/transactional applications, and as a read- intensive database for business intelligence systems.
- 4. The History of Cassandra Bigtable Dynamo
- 5. Architecture Overview Cassandra was designed with the understanding that system/hardware failures can and do occur Peer-to-peer, distributed system All nodes the same Data partitioned among all nodes in the cluster Custom data replication to ensure fault tolerance Read/Write-anywhere design
- 6. Architecture Overview Each node communicates with each other through the Gossip protocol, which exchanges information across the cluster every second A commit log is used on each node to capture write activity. Data durability is assured Data also written to an in-memory structure (memtable) and then to disk once the memory structure is full (an SStable)
- 7. Architecture Overview The schema used in Cassandra is mirrored after Google Bigtable. It is a row-oriented, column structure A keyspace is akin to a database in the RDBMS world A column family is similar to an RDBMS table but is more flexible/dynamic A row in a column family is indexed by its key. Other columns may be indexed as well Portfolio Keyspace Customer Column Family ID Name SSN DOB
- 8. Why Cassandra? Gigabyte to Petabyte scalability Linear performance gains through adding nodes No single point of failure Easy replication / data distribution Multi-data center and Cloud capable No need for separate caching layer Tunable data consistency Flexible schema design Data Compression CQL language (like SQL) Support for key languages and platforms No need for special hardware or software
- 9. Big Data Scalability Capable of comfortably scaling to petabytes New nodes = Linear performance increases Add new nodes online 1 1 2 4 Double Throughput Capabilities 2 3
- 10. No Single Point of Failure Allnodes the same Customized replication affords tunable data redundancy Read/write from any node Can replicate data among different physical data center racks
- 11. Easy Replication / Data Distribution Transparently handled by Cassandra Multi-data center capable Exploits all the benefits of Cloud computing Able to do hybrid Cloud/On-premise setup
- 12. No Need for Caching Software Peer-to-peer architecture removes need for special caching layer and the programming that goes with it The database cluster uses the memory from all participating nodes to cache the data assigned to each node No irregularities between a memory cache and database are encountered Application Servers Reads Writes Memcached Servers Database Server
- 13. Tunable Data Consistency Choose between strong and eventual consistency (All to any node responding) depending on the need Can be done on a per-operation basis, and for both reads and writes Handles Multi-data center operations 1 6 2 Writes Reads Any One 5 3 One Quorum Quorum Local_Quorum Local_Quorum Each_Quorum 4 Each_Quorum All All
- 14. Flexible Schema Dynamic schema design allows for much more flexible data storage than rigid RDBMS Handles structured, semi-structured, and unstructured data. Counters also supported No offline/downtime for schema changes Supports primary and secondary indexes Portfolio Keyspace Customer Column Family ID Name SSN DOB
- 15. Data Compression Uses Google’s Snappy data compression algorithm Compresses data on a per column family level Internal tests at DataStax show up to 80%+ compression of raw data No performance penalty (and some increases in overall performance due to less physical I/O)!
- 16. CQL Language Verysimilar to RDBMS SQL syntax Create objects via DDL (e.g. CREATE…) Core DML commands supported: INSERT, UPDATE, DELETE Query data with SELECT 1 6 2 SELECT * FROM USERS 5 WHERE STATE = ‘TX’; 3 4
- 18. Where to get Cassandra? Go to www.datastax.com DataStax makes free smart start installers available for Cassandra that include: The most up-to-date Cassandra version that is production quality A version of DataStax OpsCenter, which is a visual, browser-based management tool for managing and monitoring Cassandra Drivers and connectors for popular development languages Same database and application Automatic configuration assistance for ensuring optimal performance and setup for either stand- alone or cluster implementations Getting Started Guide
- 19. Where Can I Learn More? www.datastax.com Free Online Documentation Technical White Papers Technical Articles Tutorials User Forums User/Customer Case Studies FAQ’s Videos Blogs Software downloads
- 20. Cassandra Essentials Tutorial Series An Overview of Apache Cassandra Thanks…!